Analysis on the influencing factors of users’ usage intention and user behavior patterns in online medical community under COVID-19

Abstract

Abstract With the spread of COVID-19, the shortage and uneven distribution of medical and health resources in the traditional medical industry, as well as the vulnerability to infection, have aroused concerns. As a new way of Internet medical treatment, online medical treatment greatly alleviates the pressure of difficulty in getting medical treatment. However, few studies have explored the factors that influence users’ use of online medical communities and the patterns of users’ behavior. Based on the theory of perceived value, social support, information asymmetry and information behavior of “Type Person”, this paper constructs the influencing factor model of users’ usage intention in online medical community. Questionnaires were distributed to users in the online medical community, multiple linear regression was conducted through SPSS to test the assumptions in the model, and then user groups were clustered to analyze user behavior patterns. The results showed that perceived benefit, social support, medical effect and user trust had positive effects on users’ usage intention, while perceived risk had a negative effect on it.” Type A” users have a lower intention, “Type B” users are skeptical about medical effect, “Type C” users have a higher intention, and “Type D” users pay more attention to emotional support. Finally, this paper provides some suggestions for online medical community to improve the quality of medical information service.